Predictive value of microRNA-122 in obesity and metabolic syndrome

Background and aim Metabolic syndrome (MetS) is a collection of metabolic dysregulations such as hypertension, insulin resistance, atherogenic dyslipidemia, and central obesity. MicroRNA-122 (miR-122) was the first of the many circulating miRNAs linked to metabolic diseases and obesity. MiR-122 is a liver-enriched miRNA that influences lipid and cholesterol metabolism. This study aims to evaluate the miR-122 function in the obesity’s pathogenesis and to assess the possible association of miRNA-122 with MetS in obese patients. Patients and methods The study included 50 Egyptian individuals (20 healthy persons as control, 15 obese patients without MetS, and 15 obese patients with MetS). The levels of miR-122 were validated using quantitative reverse transcription real-time polymerase chain reaction tests. Results Serum miR-122 demonstrated a highly significant increase in obese patients collectively compared with the control ( P <0.001). Moreover, miR-122 demonstrated upregulation expression in obese cases having MetS compared with controls and the obese without MetS. There were statistically significant strong positive correlations between miR-122 expression and BMI, waist circumference, blood pressure, markers of dysglycemia, and dyslipidemia. Also, there were negative correlations with high-density lipoprotein (all having P =<0.001). Conclusion MiR-122 could be a valuable biomarker of obesity’s pathogenesis and MetS in obese patients.

Authors

Institutions

Publication Details

Journal
Al-Azhar Assiut Medical Journal
Published
2024-10-01
DOI
https://doi.org/10.4103/azmj.azmj_38_24
Primary Topic
Cardiovascular Disease and Adiposity
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive value of microRNA-122 in obesity and metabolic syndrome

Nora Seliem, Aisha H.T.M. Abdelhafez, Eman F. Mohamed, Wafaa M. Abdel Fattah
Al-Azhar Assiut Medical Journal
Cardiovascular Disease and Adiposity
article

Predictive value of microRNA-122 in obesity and metabolic syndrome

Nora Seliem, Aisha H.T.M. Abdelhafez, Eman F. Mohamed, Wafaa M. Abdel Fattah
article en

Abstract

Background and aim Metabolic syndrome (MetS) is a collection of metabolic dysregulations such as hypertension, insulin resistance, atherogenic dyslipidemia, and central obesity. MicroRNA-122 (miR-122) was the first of the many circulating miRNAs linked to metabolic diseases and obesity. MiR-122 is a liver-enriched miRNA that influences lipid and cholesterol metabolism. This study aims to evaluate the miR-122 function in the obesity’s pathogenesis and to assess the possible association of miRNA-122 with MetS in obese patients. Patients and methods The study included 50 Egyptian individuals (20 healthy persons as control, 15 obese patients without MetS, and 15 obese patients with MetS). The levels of miR-122 were validated using quantitative reverse transcription real-time polymerase chain reaction tests. Results Serum miR-122 demonstrated a highly significant increase in obese patients collectively compared with the control ( P <0.001). Moreover, miR-122 demonstrated upregulation expression in obese cases having MetS compared with controls and the obese without MetS. There were statistically significant strong positive correlations between miR-122 expression and BMI, waist circumference, blood pressure, markers of dysglycemia, and dyslipidemia. Also, there were negative correlations with high-density lipoprotein (all having P =<0.001). Conclusion MiR-122 could be a valuable biomarker of obesity’s pathogenesis and MetS in obese patients.

Al-Azhar Assiut Medical JournalVol. 22(4)
Al-Azhar University (EG), Badr University in Cairo (EG)
Openalex Percentile: Top 54%
Cardiovascular Disease and Adiposity
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.